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 » Il dipartimento » Personale
VENERE MARCO
Dottorando di Ricerca in Ingegneria dell'Informazione
[javascript protected email address]
Area di ricerca:
  • Informatica
Linea di ricerca:
  • Architetture
Marco Venere is a PhD candidate in Information Technology at Politecnico di Milano under Prof. Marco Domenico Santambrogio. His research operates at the cutting edge of quantum computing and electronic design automation (EDA), with a focus on quantum error correction, quantum algorithms for hardware design, and FPGA-based acceleration systems.

Marco's work addresses critical challenges in the quantum computing stack, from theoretical algorithm development to practical hardware implementation. His research contributions include developing a quantum approach to solve the Boolean matching problem in EDA toolchains, achieving super-polynomial speedups over classical methods through the novel Grover-meets-Simon technique. He also focused hardware acceleration for quantum error correction, designing an FPGA implementation of the Sparse Blossom Algorithm (QASBA) that achieve up to 25× speedup and 304× energy efficiency improvements. His work on qubit routing optimization (DDRoute) reduces circuit depth overhead by up to 70%, addressing a fundamental bottleneck in NISQ-era quantum computing.

Marco has over 10 publications in top venues including IEEE TQE, ACM TRETS, and DAC, and gained industry experience at AMD in Dublin (FPGA-GPU DMA infrastructure) and Inveriant/Centre for Quantum Technologies, focusing on quantum algorithms for combinatorial optimization and benchmarking quantum processing units. He served as Chair of IEEE Italy Section Student Branch and is actively involved in the research community as TPC member for IEEE QCE 2024 and 2025, reviewer for TCAD, ICCAD, ISCAS, and multiple other conferences, and session chair at QCE 2024.
His work has been recognized with a Best Poster Award at RAW 2024 and 2025, a second place at DAC 2025 PhD Forum, a UnitaryFund MicroGrant, and a Xilinx Open Hardware award. Marco also teaches quantum computing courses with NECSTLab and MathWorks, mentoring students in quantum algorithm development.

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